Leeuwenberg, A., & Moens, M. F. (2019). A survey on temporal reasoning for temporal information extraction from text. Journal of Artificial Intelligence Research, 66, 341-380.

University of Michigan - Ann Arbor

Extracting temporal cues from text, and constructing a global temporal view about the order of described events is a major challenge of automatic natural language understanding. 

Temporal reasoning (TR), the process of combining different temporal cues into a coherent temporal view, plays a central role in temporal information extraction.

Temporal Reasoning

A Survey on Temporal Reasoning for Temporal Information Extraction from Text (Extended Abstract)

Temporal Information Extraction (TIE) is the process of automatically extracting temporal cues from text, with the goal to construct a (possibly underspecified) timeline of events from them.

TIE not only plays a major role in the general problem of natural language understanding (NLU), but is also used in many applications: information retrieval, question answering, and multidocument summarization, and has great potential in the clinical domain, for applications like patient timeline visualization, forecasting treatment effects, and patient selection for clinical trials.

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